Search results

The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance.

After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns.

Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO.

This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB).

Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk.

The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications.

To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

This paper examines the short-term market impact of the beginning of the military conflict between Russia and Ukraine (February 24, 2022) on the world’s largest defense firms.

The authors examine the world’s 100 largest listed defense firms at and around the beginning of the military conflict between Russia and Ukraine using an event-study methodology.

We observe a positive and statistically significant stock price reaction at and around the beginning of the military conflict. These results are consistent with the asset-pricing perspective/expected cash flow hypothesis. Consistent with the captured regulator theory, we find superior market returns for the two portfolios with a greater weight of defense sales. Superior market returns are also found for defense firms with higher R&D and capital expenditure intensity. Finally, these reactions are reinforced or mitigated by other firm-specific characteristics such as size, profitability and institutional ownership.

The effect of the war on stock markets has been relatively little examined in the financial theory. This study intends to fill this gap in the literature.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

This study investigates the relationship between CEO leadership, gender homophily and corporate environmental, social and governance (ESG) performance. We also investigate whether it is essential to have a critical mass of women directors on the board to create a significant power of gender diversity in leadership positions.

Our study is based on firms listed on the London Stock Exchange (FTSE-All-Share) from 2011 to 2019. CEO characteristics and other board variables were collected from BoardEx, and ESG data, and other related variables were collected from Eikon database.

We find a critical mass of female directors contributes to ESG performance suggesting that token representation of female directors on boards limits their effectiveness. We do not find support for the gender homophily perspective, our findings suggest that the effectiveness of female CEOs does not depend on the existence of a critical mass of female directors. Female directors and female CEOs are less likely to be associated with ESG activities when firms experience poor financial performance. We also find that younger female CEOs have a positive impact on ESG performance. Furthermore, we find female CEOs with shorter tenure are more likely to improve ESG performance. Overall, our findings suggest a substitutional effect between having female CEOs and gender diverse boards.

This study contributes to the debate on gender homophily in the boardroom and how that may affect ESG practices. It also complements existing academic research on female leadership and ESG performance and has important implications for senior management and policymakers.

This paper aims to examine how and why consumers respond to chief executive officer (CEO) activism on social media. The authors developed a conceptual model that proposes impression management as a mechanism for consumer response to CEO activism.

In Study 1a, the authors examined 83,259 tweets from 90 CEOs and compared consumer responses between controversial and noncontroversial tweets. In Study 1b, the authors replicated the analysis, using a machine-learning topic modeling approach. In Studies 2 and 3, the authors used experimental designs to test the theoretical mechanism.

On average, consumers tend to respond more to CEO posts dealing with noncontroversial issues. Consumers’ relative reluctance to like and share controversial posts is motivated by fear of rejection. However, CEO fame reverses this effect. Consumers are more likely to engage in controversial activist threads by popular CEOs. This effect holds for consumers high (vs low) in public self-consciousness. CEO fame serves as a “shield” behind which consumers protect their online image.

The study focused on Twitter (aka “X”) in the USA. Future research may replicate the study in other social media platforms and countries. The authors introduce “shielding” – liking and sharing content authored by a recognizable source – as a tactic for impression management on social media.

Famous CEOs should speak up about controversial issues on social media because their voice helps consumers engage more in such conversations.

This paper offers a theoretical framework to understand consumer reactions to CEO activism.

This study empirically aims to examine the relationship between Bangladesh’s pharmaceutical industry growth and macroeconomic indicators such as the inflation rate, gross domestic product (GDP) growth, foreign direct investment (FDI) inflows, exchange rate and export growth through the long- and short-run relationship.

Using the time series data from 1986 to 2020, this study was developed based on the autoregressive distributed lag (ARDL) framework for co-integration. In contrast, the Toda–Yamamoto Granger Causality approach was also used for finding the direction of causality.

This study used the ARDL bounds test, which found strong co-integration among the variables, indicating a long-term relationship between them. In the long run, inflation, exchange rate and export growth significantly positively influence the pharmaceutical industry’s growth. Surprisingly, an FDI inflow has a negative impact. In the short term, the exchange rate and GDP growth were found to influence the growth of the pharmaceutical industry positively. Bidirectional causality between the growth of the pharmaceutical industry and the exchange rate was also identified using the Granger causality approach.

This paper emphasizes developing the policy as well as making concrete decisions regarding the development of the pharmaceutical industry and economic development in Bangladesh. The results also highlight the necessity for strategic macroeconomic management to support this sector’s long-term development and global competitiveness.

To the best of the authors’ knowledge, this paper is conducted to identify the short- and long-run relationship of pharmaceutical industry development with the economic indicators and progress, where no study has been found on this dimension.

This study aims to develop and test a model of the antecedents, mediators and consequences of the glass cliff phenomenon through public sector service organizations in Iran to explore more insights on gender inequality in managerial positions.

The current research was conducted based on a mixed-method approach, using both qualitative and quantitative research designs. First, the qualitative method includes content analysis by conducting semi-structured interviews with 20 university professors and expert managers working in public sector service organizations in Iran. The outcomes of the qualitative phase lead to designing the conceptual framework and research hypothesis. Then, through a quantitative phase, 384 female managers working in public sector service organizations in Iran are selected using stratified random sampling and fill out the research questionnaire. The exploratory factor analysis was used to verify the model. Moreover, structural equation modeling, using AMOS 24, was used to test the research hypothesis.

The findings of the qualitative phase were represented in three categories including antecedents (e.g. the characteristics of women’s leadership, the selection of women based on meritocracy criteria, women’s preferences and organizational factors), mediation effect (e.g. succession planning, personal development planning and support networks) and consequences of the glass cliff phenomenon (e.g. positive and negative consequences). The results of the exploratory factor analysis show there are ten components, explaining 88.5% of variances. Moreover, the test of the structural model supports the direct effect of antecedents on the glass cliff phenomenon. The results also show the effect of the glass cliff phenomenon on consequences through mediation effects.

There are some limitations that can be addressed by other researchers. Accordingly, the limited number of female managers in Iran prevented larger quantitative research. Moreover, the current research only found casual and mediation consequences of the glass cliff phenomenon, and potential moderators were not considered in this study.

The present study’s innovations may include using a mixed-method approach to investigate the antecedents, mediators and consequences of the glass cliff phenomenon in this study and examining the model constructs in some public sector service organizations. This research may provide a deep understanding of the antecedents, mediators and consequences of the glass cliff phenomenon by finding new factors using a mixed-method approach.

This study aims to examine the relationship between audit committee (AC) effectiveness and firm performance (FP) with the moderation of knowledge intensity while observing the varying effect of each AC characteristic’s influence on its effectiveness.

This study examines 133 companies covering five years from 2016 to 2020 using the partial least squares-structural equation model and weighing AC effectiveness-related characteristics through multiple regression between AC characteristics and the AC effectiveness construct.

The results indicate that the knowledge intensity of the firms negatively influences the relationship between their AC effectiveness and FP, implying that the ACs are not sophisticated enough to monitor the knowledge component of the firm’s assets. Among AC characteristics, six attributes have a significant positive impact, two have a negative impact and three have no significant influence on AC effectiveness while influencing FP.

Apart from guiding the regulators, managers and other stakeholders to choose an appropriate mix of AC characteristics for enhancing FP, the study contributes to the existing literature by providing evidence that ACs are ineffective in monitoring the knowledge assets of the company compared to physical assets.

This study is pioneering in investigating the moderation role of knowledge intensity on the relationship between AC effectiveness and FP. While providing a comprehensive and holistic view of AC effectiveness by considering 11 AC characteristics’ individual as well as aggregate effects on FP, it removes the obsolescence of earlier research in the Indian context owing to the latest regulatory reforms.

The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.

The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.

Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.

The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.